hulincup commented on issue #858:
URL: https://github.com/apache/flink-agents/issues/858#issuecomment-5394515519

   Hi @joeyutong, I'd like to take this one. The embedding providers already 
populate `EmbeddingResult.tokenUsage` (Bedrock on the Java side, OpenAI/Tongyi 
on the Python cross-lang side), but nothing reads it to record metrics. I plan 
to mirror the chat path — add `recordTokenMetrics` to `BaseEmbeddingModelSetup` 
and record `promptTokens`/`totalTokens` at the `embedWithUsage` chokepoint, so 
direct calls and vector-store/RAG paths are both covered. Pure-Python embedding 
integrations stay unchanged, consistent with the chat side having no Python 
metric layer. Happy to adjust the scope if you had something broader in mind.


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